Using static suffix array in dynamic application: Case of text compression by longest first substitution

Over the last decade, enhanced suffix arrays (ESA) have replaced suffix trees in many applications. Algorithms based on ESAs require less space, while allowing the same time efficiency as those based on suffix trees. However, this is only true when a suffix structure is used as a static index. Suffix trees can be updated faster than suffix arrays, which is a clear advantage in applications that require dynamic indexing. We show that for some dynamic applications a suffix array and the derived LCP-interval tree can be used in such a way that the actual index updates are not necessary. We demonstrate this in the case of grammar text compression with longest first substitution and provide the source code. The proposed algorithm has O(N²)$O(N^2)$ worst case time complexity but runs in O(N)$O(N)$ time in practice.     

Intelligent forest fire monitoring system

This paper presents iForestFire, an Environmental Monitoring Information System for forest fire protection. The system is composed of several components, each having a particular function. Automatic fire detection is a crucial component of the system. It is based on various complex image processing algorithms. Complexity of the system also emerges from integration, based on multi agent technology, of different environment information. The presented system contributes to the environment protection and is in use in Croatia for several years.     

Forecasting hourly $${\hbox {NO}_{2}}$$ concentrations by ensembling neural networks and mesoscale models

In the framework of extreme pollution concentrations being more and more frequent in many cities nowadays, air quality forecasting is crucial to protect public health through the anticipation of unpopular measures like traffic restrictions. In this work, we develop the core of a 48 h ahead forecasting system which is being deployed for the city of Madrid. To this end, we investigate the predictive power of a set of neural network models, including several families of deep networks, applied to the task of predicting nitrogen dioxide concentrations in an urban environment. Careful feature engineering on a set of related magnitudes as meteorology and traffic has proven useful, and we have coupled these neural models with mesoscale numerical pollution forecasts, which improve precision by up to 10%. The experiments show that some neural networks and ensembles consistently outperform the reference models, particularly improving the Naive model’s results from around (20%) up to (57%) for longer forecasting horizons. However, results also reveal that deeper networks are not particularly better than shallow ones in this setting.

     

Comparative study of decay ratios of disturbance-rejection magnitude optimum method for PI controllers

One of the key time-domain closed-loop performance requirements is the closed-loop response decay ratio. In this paper, the decay ratios of the disturbance-rejection magnitude optimum (DRMO) tuning method [Vranci? D, Strmcnik S, Kocijan J. Improving disturbance rejection of PI controllers by means of the magnitude optimum method. ISA Trans 2004; 43: 73-84; Vranci? D, Strmcnik S. Achieving optimal disturbance rejection by using the magnitude optimum method. In: Pre-prints of the CSCC'99 conference. 1999. p. 3401-6] are analyzed and compared to decay ratios of two other modern tuning methods, i.e. the Kappa-Tau tuning method (based on time-domain step-response characteristics) [Astr?m KJ, H?gglund T. PID controllers: Theory, design, and tuning. 2nd ed. Instrument Society of America; 1995] and the non-convex optimization tuning method (based on frequency response) [Panagopoulos H, Astr?m KJ, H?gglund T. Design of PI controllers based on non-convex optimization. Automatica 1998; 34: 585-601; Panagopoulos H, Astr?m KJ, H?gglund T. Design of PID controllers based on constrained optimisation. IEE Proc Control Theory Appl 2002; 149 (1): 32-40]. It is shown that the DRMO method results in such a closed-loop response that the decay ratio is within a relatively narrow interval when compared to the other two methods.     

Factors affecting the microbial populations at full-scale enhanced biological phosphorus removal (EBPR) wastewater treatment plants in The Netherlands

The influence of operating and environmental conditions on the microbial populations of the enhanced biological phosphorus removal (EBPR) process at seven full-scale municipal activated sludge wastewater treatment plants (WWTPs) in The Netherlands was studied. Data from the selected WWTPs concerning process configuration, operating and environmental conditions were compiled. The EBPR activity from each plant was determined by execution of anaerobic-anoxic-aerobic batch tests using fresh activated sludge. Fractions of Accumulibacter as potential phosphorus accumulating organisms (PAO), and Competibacter, Defluviicoccus-related microorganisms and Sphingomonas as potential glycogen accumulating organisms (GAO) were quantified using fluorescence in situ hybridization (FISH). The relationships among plant process configurations, operating parameters, environmental conditions, EBPR activity and microbial populations fractions were evaluated using a statistical approach. A well-defined and operated denitrification stage and a higher mixed liquor pH value in the anaerobic stage were positively correlated with the occurrence of Accumulibacter. A well-defined denitrification stage also stimulated the development of denitrifying PAO (DPAO). A positive correlation was observed between Competibacter fractions and organic matter concentrations in the influent. Nevertheless, Competibacter did not cause a major effect on the EBPR performance. The observed Competibacter fractions were not in the range that would have led to EBPR deterioration. Likely, the low average sewerage temperature (12+/-2 degrees C) limited their proliferation. Defluviicoccus-related microorganisms were seen only in negligible fractions in a few plants (<0.1% as EUB), whereas Sphingomonas were not observed.     

Pd[tBuNH(S)NHP(O)(OiPr)2-S]2Cl2 Complex as Air- and Moisture-Stable Catalyst for Palladium Catalyzed Suzuki Cross-Coupling Reaction

A highly efficient Suzuki cross-coupling reaction between phenyl bromide and phenylboronic acid catalyzed by the palladium complex Pd[tBuNH(S)NHP(O)(OiPr)₂-S]₂Cl₂ in acetonitrile, toluene, THF or DMF has been investigated. The bases we have employed for this reaction were Na₂CO₃, K₂CO₃ or Cs₂CO₃. It was established that using DMF and K₂CO₃ at 100 °C shows excellent yields of the product at the catalyst amount of 0.1 mmol. The cross-coupling reactions of iodo- and chloro-benzene with phenylboronic acid were also investigated. The influence of the halide nature was as expected.